Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/aim/wpaimx/1523.html
   My bibliography  Save this paper

Star Wars: The Empirics Strike Back

Author

Listed:
Abstract
Journals favor rejection of the null hypothesis. This selection upon tests may distort the behavior of researchers. Using 50,000 tests published between 2005 and 2011 in the AER, JPE, and QJE, we identify a residual in the distribution of tests that cannot be explained by selection. The distribution of p-values exhibits a two humped camel shape with abundant p-values above 0.25, a valley between 0.25 and 0.10, and a bump slightly below 0.05. The missing tests (with p-values between 0.25 and 0.10) can be retrieved just after the 0.05 threshold and represent 10% to 20% of marginally rejected tests. Our interpretation is that researchers might be tempted to inflate the value of those just-rejected tests by choosing a “significant” specification. We propose a method to measure this residual and describe how it varies by article and author characteristics.

Suggested Citation

  • Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2015. "Star Wars: The Empirics Strike Back," AMSE Working Papers 1523, Aix-Marseille School of Economics, France, revised May 2015.
    • Handle: RePEc:aim:wpaimx:1523
    as

    Download full text from publisher

    File URL: http://www.amse-aixmarseille.fr/sites/default/files/_dt/2012/wp_2015_-_nr_23.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," American Economic Review, American Economic Association, vol. 94(2), pages 454-460, May.
    2. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    3. B.D. McCullough & Kerry Anne McGeary & Teresa D. Harrison, 2008. "Do economics journal archives promote replicable research?," Canadian Journal of Economics, Canadian Economics Association, vol. 41(4), pages 1406-1420, November.
    4. Gerber, Alan & Malhotra, Neil, 2008. "Do Statistical Reporting Standards Affect What Is Published? Publication Bias in Two Leading Political Science Journals," Quarterly Journal of Political Science, now publishers, vol. 3(3), pages 313-326, October.
    5. repec:hal:spmain:info:hdl:2441/eu4vqp9ompqllr09iatr74eao is not listed on IDEAS
    6. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," American Economic Review, American Economic Association, vol. 94(2), pages 454-460, May.
    7. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    8. Ashenfelter, Orley & Harmon, Colm & Oosterbeek, Hessel, 1999. "A review of estimates of the schooling/earnings relationship, with tests for publication bias," Labour Economics, Elsevier, vol. 6(4), pages 453-470, November.
    9. Emeric Henry, 2009. "Strategic Disclosure of Research Results: The Cost of Proving Your Honesty," Economic Journal, Royal Economic Society, vol. 119(539), pages 1036-1064, July.
    10. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    11. Orley Ashenfelter & Michael Greenstone, 2004. "Estimating the Value of a Statistical Life: The Importance of Omitted Variables and Publication Bias," Working Papers 858, Princeton University, Department of Economics, Industrial Relations Section..
    12. Eric Luis Uhlmann & Anthony Bastardi & Lee Ross, 2011. "Wishful Thinking: Belief, Desire, and the Motivated Evaluation of Scientific Evidence," Post-Print hal-00609541, HAL.
    13. Dewald, William G & Thursby, Jerry G & Anderson, Richard G, 1986. "Replication in Empirical Economics: The Journal of Money, Credit and Banking Project," American Economic Review, American Economic Association, vol. 76(4), pages 587-603, September.
    14. Weiß Bernd & Wagner Michael, 2011. "The Identification and Prevention of Publication Bias in the Social Sciences and Economics," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 661-684, October.
    15. Emeric Henry, 2009. "Disclosure of research results: the cost of proving your honesty," Post-Print hal-01023670, HAL.
    16. Eva Vivalt, 2020. "How Much Can We Generalize From Impact Evaluations?," Journal of the European Economic Association, European Economic Association, vol. 18(6), pages 3045-3089.
    17. Mario Forni & Luca Gambetti & Marco Lippi & Luca Sala, 2017. "Noise Bubbles," Economic Journal, Royal Economic Society, vol. 127(604), pages 1940-1976, September.
    18. Card, David & Krueger, Alan B, 1995. "Time-Series Minimum-Wage Studies: A Meta-analysis," American Economic Review, American Economic Association, vol. 85(2), pages 238-243, May.
    19. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    20. repec:pri:cepsud:97ashenfelter is not listed on IDEAS
    21. De Long, J Bradford & Lang, Kevin, 1992. "Are All Economic Hypotheses False?," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1257-1272, December.
    22. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, July.
    23. Doucouliagos, Chris & Stanley, T.D. & Giles, Margaret, 2012. "Are estimates of the value of a statistical life exaggerated?," Journal of Health Economics, Elsevier, vol. 31(1), pages 197-206.
    24. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    25. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    26. David Card & Stefano DellaVigna, 2013. "Nine Facts about Top Journals in Economics," Journal of Economic Literature, American Economic Association, vol. 51(1), pages 144-161, March.
    27. Martin Dufwenberg & Peter Martinsson, 2014. "Keeping Researchers Honest: The Case for Sealed-Envelope-Submissions," Working Papers 533, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    28. Eva Vivalt, 0. "How Much Can We Generalize From Impact Evaluations?," Journal of the European Economic Association, European Economic Association, vol. 18(6), pages 3045-3089.
    29. David F. Hendry & Hans‐Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    30. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-317, May.
    31. Tomáš Havránek, 2015. "Measuring Intertemporal Substitution: The Importance Of Method Choices And Selective Reporting," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1180-1204, December.
    32. repec:fth:prinin:425 is not listed on IDEAS
    33. David Card & Stefano DellaVigna, 2014. "Page Limits on Economics Articles: Evidence from Two Journals," Journal of Economic Perspectives, American Economic Association, vol. 28(3), pages 149-168, Summer.
    34. Auspurg Katrin & Hinz Thomas, 2011. "What Fuels Publication Bias?: Theoretical and Empirical Analyses of Risk Factors Using the Caliper Test," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 636-660, October.
    35. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    36. Orley Ashenfelter & Colm Harmon & Hessel Oosterbeek, 1999. "A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias," Working Papers 804, Princeton University, Department of Economics, Industrial Relations Section..
    37. Chris Doucouliagos & T.D. Stanley, 2013. "Are All Economic Facts Greatly Exaggerated? Theory Competition And Selectivity," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 316-339, April.
    38. Benjamin A. Olken, 2015. "Promises and Perils of Pre-analysis Plans," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 61-80, Summer.
    39. Daniele Fanelli, 2009. "How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data," PLOS ONE, Public Library of Science, vol. 4(5), pages 1-11, May.
    40. repec:hal:wpspec:info:hdl:2441/eu4vqp9ompqllr09iatr74eao is not listed on IDEAS
    41. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cristina Blanco-Perez & Abel Brodeur, 2020. "Publication Bias and Editorial Statement on Negative Findings," The Economic Journal, Royal Economic Society, vol. 130(629), pages 1226-1247.
    2. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    3. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    4. Abel Brodeur & Nikolai Cook & Anthony Heyes, 2020. "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics," American Economic Review, American Economic Association, vol. 110(11), pages 3634-3660, November.
    5. Dominika Ehrenbergerova & Josef Bajzik & Tomas Havranek, 2023. "When Does Monetary Policy Sway House Prices? A Meta-Analysis," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 538-573, June.
    6. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    7. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2018. "Methods Matter: P-Hacking and Causal Inference in Economics," IZA Discussion Papers 11796, Institute of Labor Economics (IZA).
    8. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).
    9. Roman Horvath & Ali Elminejad & Tomas Havranek, 2020. "Publication and Identification Biases in Measuring the Intertemporal Substitution of Labor Supply," Working Papers IES 2020/32, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    10. Stephan B. Bruns, 2013. "Identifying Genuine Effects in Observational Research by Means of Meta-Regressions," Jena Economics Research Papers 2013-040, Friedrich-Schiller-University Jena.
    11. Sebastian Gechert & Tomas Havranek & Zuzana Irsova & Dominika Kolcunova, 2022. "Measuring Capital-Labor Substitution: The Importance of Method Choices and Publication Bias," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 55-82, July.
    12. Tomas Havranek & Anna Sokolova, 2016. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 130 Studies Say "Probably Not"," Working Papers 2016/08, Czech National Bank.
    13. Tomas Havranek, 2013. "Publication Bias in Measuring Intertemporal Substitution," Working Papers IES 2013/15, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2013.
    14. Ali Elminejad & Tomas Havranek & Roman Horvath & Zuzana Irsova, 2023. "Intertemporal Substitution in Labor Supply: A Meta-Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 1095-1113, December.
    15. Chris Doucouliagos & T.D. Stanley, 2013. "Are All Economic Facts Greatly Exaggerated? Theory Competition And Selectivity," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 316-339, April.
    16. Stephan B. Bruns, 2016. "The Fragility of Meta-Regression Models in Observational Research," MAGKS Papers on Economics 201603, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    17. Tomas Havranek & Anna Sokolova, 2020. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 144 Studies Say 'Probably Not'," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 35, pages 97-122, January.
    18. Christopher Snyder & Ran Zhuo, 2018. "Sniff Tests as a Screen in the Publication Process: Throwing out the Wheat with the Chaff," NBER Working Papers 25058, National Bureau of Economic Research, Inc.
    19. Abel Brodeur & Scott Carrell & David Figlio & Lester Lusher, 2023. "Unpacking P-hacking and Publication Bias," American Economic Review, American Economic Association, vol. 113(11), pages 2974-3002, November.
    20. Bobtcheff, Catherine & Mariotti, Thomas & Levy, Raphaël, 2021. "Negative results in science: Blessing or (winner’s) curse," TSE Working Papers 21-1202, Toulouse School of Economics (TSE).

    More about this item

    Keywords

    hypothesis testing; distorting incentives; selection bias; research in economics;
    All these keywords.

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aim:wpaimx:1523. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gregory Cornu (email available below). General contact details of provider: https://edirc.repec.org/data/amseafr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.